Automatic Identification of Arabic expressions related to future events in Lebanon's economy

In this paper, we propose a method to automatically identify future events in Lebanon's economy from Arabic texts. Challenges are threefold: first, we need to build a corpus of Arabic texts that covers Lebanon's economy; second, we need to study how future events are expressed linguistically in these texts; and third, we need to automatically identify the relevant textual segments accordingly. We will validate this method on a constructed corpus form the web and show that it has very promising results. To do so, we will be using SLCSAS, a system for semantic analysis, based on the Contextual Explorer method, and "AlKhalil Morpho Sys" system for morpho-syntactic analysis.

Automatic Annotation of Locative and Directional Expressions in Arabic

In this paper, we introduce a rule-based approach to annotate Locative and Directional Expressions in Arabic natural language text. The annotation is based on a constructed semantic map of the spatiality domain. Challenges are twofold: first, we need to study how locative and directional expressions are expressed linguistically in these texts; and second, we need to automatically annotate the relevant textual segments accordingly. The research method we will use in this article is analytic-descriptive. We will validate this approach on specific novel rich with these expressions and show that it has very promising results. We will be using NOOJ as a software tool to implement finite-state transducers to annotate linguistic elements according to Locative and Directional Expressions. In conclusion, NOOJ allowed us to write linguistic rules for the automatic annotation in Arabic text of Locative and Directional Expressions.